---
title: "Covid Timeline India - Gautam Malhotra"
output:
flexdashboard::flex_dashboard:
orientation: columns
vertical_layout: fill
source_code: embed
theme: cerulean
---
```{r setup, include=FALSE}
library(flexdashboard)
```
#Calculations
```{r}
library(dplyr)
library(dygraphs)
library(lubridate)
library(ggplot2)
library(tidyverse)
library(gganimate)
library(gifski)
library(av)
data<-read.csv("owid-covid-data.csv")
I<-data %>% filter(location=="India")
India_covid<-data %>% filter(location=="India")
India_covid<-data.frame(cases=India_covid$new_cases_smoothed_per_million,deaths=India_covid$new_deaths_smoothed_per_million,gdp=India_covid$gdp_per_capita)
India_covid<-na.omit(India_covid)
cases<-ts(India_covid$cases)
deaths<-ts(India_covid$deaths)
India<-cbind(cases,deaths)
total<-data %>% filter(location=="India")
total<-ts(na.omit(total$total_deaths))
new_cases<-ts(na.omit(I$new_cases))
new_deaths<-ts(na.omit(I$new_deaths))
```
Visual {data-orientation=rows}
=====================================
Row {data-width=650}
-----------------------------------------------------------------------
### New Cases per Million Vs New Deaths per Million
```{r}
dygraph(India,main="Cases per Million Vs Deaths per Million")%>%
dyHighlight(highlightCircleSize = 5,
highlightSeriesBackgroundAlpha = 0.2,
hideOnMouseOut = FALSE)
```
Row {data-width=650}
-----------------------------------------------------------------------
### Total Deaths
```{r}
dygraph(total,main="Total Deaths") %>% dySeries("V1", label = "Deaths") %>%
dyLegend(show = "follow") %>% dyRangeSelector()
```
Representations {data-orientation=rows}
=====================================
Row
-------------------------------------
### New Cases
```{r}
dygraph(new_cases,main="New Cases",group = "a") %>% dySeries("V1", label = "Cases")
```
Row
-------------------------------------
### New Cases
```{r}
dygraph(new_deaths,main="New Deaths",group = "a") %>% dySeries("V1", label = "Deaths")
```
Representations {data-orientation=rows}
=====================================
Row
-----------------------------------------------------------------------
### Daily Cumilative Cases
```{r}
new_data<-data %>% filter(location=="India") %>% group_by(date)
new_data<-summarise(new_data,new=replace_na(new_cases,0),cuml=cumsum(new))
new_data %>% ggplot(aes(x = date, y = cuml)) +geom_point(size=0.5,color="red") +
geom_line()+
ggtitle("Daily Cumilative Cases")
```
